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Proceedings Paper

Effects of fixed-rate CT projection data compression on perceived and measured CT image quality
Author(s): Albert Wegener; Naveen Chandra; Yi Ling; Robert Senzig; Robert Herfkens
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Paper Abstract

Compression of computed tomography (CT) projection data reduces CT scanner bandwidth and storage costs. Since fixed-rate compression guarantees predictable bandwidth, fixed-rate compression is preferable to lossless compression, but fixed-rate compression can introduce image artifacts. This research demonstrates clinically acceptable image quality at 3:1 compression as judged by a radiologist and as estimated by an image quality metric called local structural similarity (SSIM). We examine other common, quantitative image quality metrics from image processing, including peak signal-to-noise (PSNR), contrast-to-noise ratio (CNR), and difference image statistics to quantify the magnitude and location of image artifacts caused by fixed-rate compression of CT projection data. Masking effects caused by local contrast, air and bone pixels, and image reconstruction effects at the image's periphery and iso-center explain why artifacts introduced by compression are not noticed by radiologists. SSIM metrics in this study nearly always exceeds 0.98 (even at 4:1 compression ratios), which is considered visually indistinguishable. The excellent correlation of local SSIM and subjective image quality assessment confirms that fixed-rate 3:1 projection data compression on CT images does not affect clinical diagnosis and is rarely noticed. Local SSIM metrics can be used to significantly reduce the number of viewed images in medical image quality studies.

Paper Details

Date Published: 24 February 2010
PDF: 12 pages
Proc. SPIE 7627, Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment, 76270G (24 February 2010); doi: 10.1117/12.841145
Show Author Affiliations
Albert Wegener, Samplify Systems (United States)
Naveen Chandra, GE Healthcare (United States)
Yi Ling, Samplify Systems (United States)
Robert Senzig, GE Healthcare (United States)
Robert Herfkens, Stanford Univ. School of Medicine (United States)


Published in SPIE Proceedings Vol. 7627:
Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment
David J. Manning; Craig K. Abbey, Editor(s)

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